A4_Past_TT

A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

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Report generated on 2022-11-09, 17:17 based on data in: /glfs/brick01/gv0/putnamlab/kevin_wong1/Thermal_Transplant_WGBS/methylseq_A4/A4_Past_TT

General Statistics

Showing ¹⁸⁸/₁₈₈ rows and ¹⁷/₂₇ columns.

Sample Name	% GC	Ins. size	≥ 1X	≥ 5X	≥ 10X	≥ 30X	≥ 50X	Median cov	Mean cov	% Aligned	M Aligned	M Total reads	Error rate	% mCpG	% mCHG	% mCHH	M C's	% Dups	M Unique	M Aligned	% Aligned	% BP Trimmed	% Dups	% GC	Length	% Failed	M Seqs
18-106_S163_L004_R1_001																						15.7%	17.5%	28%	151 bp	18%	52.8
18-106_S163_L004_R1_001_val_1	30%	71	14.7%	0.5%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	3.3	3.3	27.26%	31.5%	3.4%	11.5%	34.3	15.4%	1.6	1.9	3.7%		17.4%	22%	108 bp	0%	52.5
18-106_S163_L004_R2_001																						15.6%	17.3%	28%	151 bp	9%	52.8
18-106_S163_L004_R2_001_val_2																							17.3%	22%	108 bp	0%	52.5
18-118_S162_L004_R1_001																						13.7%	20.5%	27%	151 bp	18%	59.7
18-118_S162_L004_R1_001_val_1	29%	68	8.6%	0.2%	0.0%	0.0%	0.0%	0.0X	0.2X	100.0%	1.9	1.9	27.80%	32.0%	3.3%	14.7%	19.2	17.7%	0.9	1.1	1.9%		20.6%	22%	111 bp	0%	59.4
18-118_S162_L004_R2_001																						13.7%	20.3%	27%	151 bp	9%	59.7
18-118_S162_L004_R2_001_val_2																							20.5%	22%	111 bp	0%	59.4
18-130_S172_L004_R1_001																						29.4%	18.4%	34%	151 bp	27%	63.0
18-130_S172_L004_R1_001_val_1	31%	56	20.5%	1.2%	0.3%	0.0%	0.0%	0.0X	0.6X	100.0%	6.0	6.0	27.05%	29.9%	4.2%	17.1%	51.7	13.1%	3.0	3.4	5.8%		13.0%	24%	92 bp	0%	58.8
18-130_S172_L004_R2_001																						29.1%	17.9%	33%	151 bp	27%	63.0
18-130_S172_L004_R2_001_val_2																							12.9%	24%	93 bp	0%	58.8
18-142_S189_L004_R1_001																						19.5%	18.2%	29%	151 bp	18%	54.0
18-142_S189_L004_R1_001_val_1	30%	65	13.0%	0.4%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	3.2	3.2	27.59%	29.6%	3.2%	14.7%	30.7	13.1%	1.6	1.8	3.5%		16.2%	22%	104 bp	0%	52.7
18-142_S189_L004_R2_001																						19.3%	17.9%	29%	151 bp	27%	54.0
18-142_S189_L004_R2_001_val_2																							16.1%	23%	104 bp	0%	52.7
18-167_S166_L004_R1_001																						15.8%	12.9%	28%	151 bp	9%	37.2
18-167_S166_L004_R1_001_val_1	30%	70	8.7%	0.2%	0.0%	0.0%	0.0%	0.0X	0.2X	100.0%	1.8	1.8	27.68%	31.0%	3.2%	13.0%	19.1	12.1%	0.9	1.0	2.8%		13.0%	23%	108 bp	0%	36.9
18-167_S166_L004_R2_001																						15.6%	13.2%	28%	151 bp	18%	37.2
18-167_S166_L004_R2_001_val_2																							13.3%	23%	108 bp	0%	36.9
18-178_S191_L004_R1_001																						20.1%	19.9%	30%	151 bp	18%	64.1
18-178_S191_L004_R1_001_val_1	30%	64	13.8%	0.5%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	3.4	3.4	27.46%	33.9%	3.5%	15.4%	32.9	15.8%	1.7	2.0	3.3%		18.0%	23%	103 bp	0%	62.7
18-178_S191_L004_R2_001																						19.9%	20.0%	30%	151 bp	27%	64.1
18-178_S191_L004_R2_001_val_2																							18.1%	23%	103 bp	0%	62.7
18-190_S186_L004_R1_001																						18.2%	24.5%	29%	151 bp	18%	60.3
18-190_S186_L004_R1_001_val_1	30%	67	15.0%	0.6%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	3.5	3.5	27.36%	32.7%	3.2%	12.5%	35.6	21.4%	1.8	2.2	3.8%		22.4%	22%	106 bp	0%	58.8
18-190_S186_L004_R2_001																						18.1%	24.3%	29%	151 bp	27%	60.3
18-190_S186_L004_R2_001_val_2																							22.4%	23%	106 bp	0%	58.8
18-202_S188_L004_R1_001																						20.0%	17.9%	30%	151 bp	18%	45.8
18-202_S188_L004_R1_001_val_1	30%	63	11.9%	0.4%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	2.8	2.8	27.47%	32.9%	3.3%	14.2%	27.2	13.3%	1.4	1.6	3.7%		15.5%	23%	104 bp	0%	44.5
18-202_S188_L004_R2_001																						19.8%	17.8%	30%	151 bp	27%	45.8
18-202_S188_L004_R2_001_val_2																							15.4%	23%	104 bp	0%	44.5
18-20_S202_L004_R1_001																						17.1%	22.8%	29%	151 bp	18%	54.3
18-20_S202_L004_R1_001_val_1	30%	63	11.0%	0.3%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	2.6	2.6	27.79%	30.9%	3.2%	13.6%	25.3	18.1%	1.3	1.6	3.0%		20.7%	22%	109 bp	0%	52.5
18-20_S202_L004_R2_001																						17.0%	22.6%	29%	151 bp	27%	54.3
18-20_S202_L004_R2_001_val_2																							20.5%	23%	109 bp	9%	52.5
18-227_S170_L004_R1_001																						29.1%	20.7%	34%	151 bp	27%	64.2
18-227_S170_L004_R1_001_val_1	30%	38	11.4%	0.6%	0.2%	0.0%	0.0%	0.0X	0.3X	100.0%	3.9	3.9	28.85%	26.9%	4.3%	23.7%	29.3	16.5%	1.9	2.3	3.8%		15.3%	23%	93 bp	0%	60.2
18-227_S170_L004_R2_001																						28.9%	20.8%	34%	151 bp	27%	64.2
18-227_S170_L004_R2_001_val_2																							15.6%	23%	93 bp	0%	60.2
18-239_S185_L004_R1_001																						23.3%	21.4%	32%	151 bp	18%	59.0
18-239_S185_L004_R1_001_val_1	30%	52	12.0%	0.5%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	3.3	3.3	28.03%	30.8%	3.5%	18.2%	28.7	16.5%	1.7	2.0	3.6%		16.8%	23%	101 bp	0%	55.7
18-239_S185_L004_R2_001																						23.0%	21.2%	31%	151 bp	27%	59.0
18-239_S185_L004_R2_001_val_2																							17.1%	23%	102 bp	0%	55.7
18-250_S195_L004_R1_001																						20.5%	19.7%	29%	151 bp	18%	72.5
18-250_S195_L004_R1_001_val_1	30%	44	9.7%	0.4%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	2.9	2.9	28.91%	26.8%	3.6%	23.3%	24.4	16.4%	1.5	1.8	2.5%		17.5%	22%	103 bp	0%	70.6
18-250_S195_L004_R2_001																						20.3%	19.8%	29%	151 bp	27%	72.5
18-250_S195_L004_R2_001_val_2																							17.8%	23%	103 bp	0%	70.6
18-262_S179_L004_R1_001																						21.1%	16.3%	29%	151 bp	9%	80.7
18-262_S179_L004_R1_001_val_1	30%	52	15.0%	0.7%	0.2%	0.0%	0.0%	0.0X	0.4X	100.0%	4.2	4.2	28.29%	32.0%	3.3%	18.0%	37.5	13.8%	2.1	2.4	3.0%		15.5%	22%	100 bp	0%	80.0
18-262_S179_L004_R2_001																						20.9%	16.3%	30%	151 bp	27%	80.7
18-262_S179_L004_R2_001_val_2																							15.5%	22%	100 bp	0%	80.0
18-311_S187_L004_R1_001																						19.9%	20.8%	30%	151 bp	27%	70.9
18-311_S187_L004_R1_001_val_1	30%	61	14.5%	0.6%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	3.8	3.8	27.51%	34.3%	3.3%	15.9%	34.8	17.5%	1.9	2.3	3.3%		18.9%	22%	103 bp	0%	69.3
18-311_S187_L004_R2_001																						19.8%	20.9%	29%	151 bp	18%	70.9
18-311_S187_L004_R2_001_val_2																							19.3%	23%	103 bp	0%	69.3
18-322_S180_L004_R1_001																						18.2%	15.1%	29%	151 bp	9%	65.3
18-322_S180_L004_R1_001_val_1	30%	67	11.5%	0.4%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	2.7	2.7	28.20%	29.9%	3.3%	16.0%	27.3	12.2%	1.4	1.6	2.4%		14.8%	23%	104 bp	0%	64.9
18-322_S180_L004_R2_001																						18.0%	14.9%	29%	151 bp	9%	65.3
18-322_S180_L004_R2_001_val_2																							14.7%	23%	104 bp	0%	64.9
18-32_S178_L004_R1_001																						20.2%	15.7%	30%	151 bp	9%	64.4
18-32_S178_L004_R1_001_val_1	30%	67	24.3%	1.6%	0.3%	0.0%	0.0%	0.0X	0.6X	100.0%	6.2	6.2	27.33%	32.6%	3.2%	11.3%	62.5	12.5%	3.1	3.5	5.6%		15.3%	23%	102 bp	0%	63.6
18-32_S178_L004_R2_001																						20.0%	15.4%	29%	151 bp	18%	64.4
18-32_S178_L004_R2_001_val_2																							15.0%	23%	102 bp	0%	63.6
18-334_S164_L004_R1_001																						8.2%	11.4%	24%	151 bp	18%	16.4
18-334_S164_L004_R1_001_val_1	29%	79	2.5%	0.0%	0.0%	0.0%	0.0%	0.0X	0.0X	100.0%	0.4	0.4	27.65%	32.5%	3.1%	11.0%	5.1	9.1%	0.2	0.2	1.4%		12.1%	21%	119 bp	0%	16.3
18-334_S164_L004_R2_001																						8.3%	11.4%	25%	151 bp	9%	16.4
18-334_S164_L004_R2_001_val_2																							12.0%	22%	119 bp	0%	16.3
18-346_S193_L004_R1_001																						17.2%	22.9%	28%	151 bp	9%	77.1
18-346_S193_L004_R1_001_val_1	30%	63	16.1%	0.7%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	4.0	4.0	27.66%	31.6%	3.2%	13.2%	39.2	19.2%	2.0	2.5	3.3%		21.5%	22%	107 bp	0%	75.4
18-346_S193_L004_R2_001																						17.1%	23.1%	28%	151 bp	18%	77.1
18-346_S193_L004_R2_001_val_2																							21.8%	22%	107 bp	0%	75.4
18-358_S201_L004_R1_001																						21.5%	25.5%	31%	151 bp	18%	71.4
18-358_S201_L004_R1_001_val_1	30%	63	14.8%	0.6%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	3.7	3.7	28.04%	27.7%	3.2%	14.5%	36.0	22.7%	1.8	2.4	3.5%		22.8%	23%	102 bp	0%	68.5
18-358_S201_L004_R2_001																						21.2%	25.3%	31%	151 bp	27%	71.4
18-358_S201_L004_R2_001_val_2																							22.8%	24%	103 bp	0%	68.5
18-370_S171_L004_R1_001																						23.2%	18.8%	32%	151 bp	27%	65.2
18-370_S171_L004_R1_001_val_1	30%	62	23.5%	1.4%	0.3%	0.0%	0.0%	0.0X	0.6X	100.0%	6.2	6.2	26.70%	31.8%	3.7%	13.1%	59.2	13.0%	3.1	3.6	5.8%		15.2%	23%	100 bp	0%	62.2
18-370_S171_L004_R2_001																						22.9%	18.0%	31%	151 bp	27%	65.2
18-370_S171_L004_R2_001_val_2																							14.7%	23%	101 bp	0%	62.2
18-394_S192_L004_R1_001																						18.6%	17.3%	30%	151 bp	18%	50.7
18-394_S192_L004_R1_001_val_1	30%	63	9.8%	0.3%	0.1%	0.0%	0.0%	0.0X	0.2X	100.0%	2.3	2.3	28.05%	29.1%	3.2%	15.7%	22.7	13.3%	1.2	1.4	2.8%		15.5%	22%	106 bp	0%	49.2
18-394_S192_L004_R2_001																						18.4%	16.9%	29%	151 bp	27%	50.7
18-394_S192_L004_R2_001_val_2																							15.4%	23%	106 bp	0%	49.2
18-406_S177_L004_R1_001																						18.3%	16.7%	28%	151 bp	9%	64.0
18-406_S177_L004_R1_001_val_1	30%	58	11.4%	0.4%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	2.9	2.9	28.56%	28.0%	3.2%	17.4%	27.5	13.4%	1.5	1.7	2.7%		16.3%	22%	104 bp	0%	63.4
18-406_S177_L004_R2_001																						18.1%	16.4%	29%	151 bp	27%	64.0
18-406_S177_L004_R2_001_val_2																							15.9%	22%	105 bp	0%	63.4
18-418_S196_L004_R1_001																						20.2%	20.6%	30%	151 bp	18%	62.8
18-418_S196_L004_R1_001_val_1	30%	62	15.7%	0.7%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	4.0	4.0	27.72%	28.2%	3.2%	14.5%	38.3	17.0%	2.0	2.4	4.0%		18.7%	22%	103 bp	0%	61.1
18-418_S196_L004_R2_001																						20.0%	20.6%	30%	151 bp	27%	62.8
18-418_S196_L004_R2_001_val_2																							18.9%	23%	103 bp	9%	61.1
18-442_S165_L004_R1_001																						10.3%	21.4%	25%	151 bp	18%	85.3
18-442_S165_L004_R1_001_val_1	29%	80	20.5%	0.9%	0.1%	0.0%	0.0%	0.0X	0.5X	100.0%	4.2	4.2	26.86%	37.6%	3.0%	9.6%	49.5	15.7%	2.1	2.5	2.9%		22.3%	21%	116 bp	0%	84.9
18-442_S165_L004_R2_001																						10.3%	20.7%	25%	151 bp	9%	85.3
18-442_S165_L004_R2_001_val_2																							21.5%	22%	116 bp	9%	84.9
18-44_S198_L004_R1_001																						15.1%	20.7%	28%	151 bp	9%	68.2
18-44_S198_L004_R1_001_val_1	30%	71	16.7%	0.7%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	3.8	3.8	27.31%	32.8%	2.8%	11.7%	40.3	16.0%	1.9	2.3	3.4%		19.8%	22%	110 bp	0%	67.0
18-44_S198_L004_R2_001																						15.0%	20.8%	28%	151 bp	18%	68.2
18-44_S198_L004_R2_001_val_2																							19.9%	22%	110 bp	9%	67.0
18-454_S197_L004_R1_001																						17.3%	22.8%	28%	151 bp	18%	81.6
18-454_S197_L004_R1_001_val_1	30%	76	22.2%	1.3%	0.2%	0.0%	0.0%	0.0X	0.6X	100.0%	5.2	5.2	27.30%	28.4%	3.1%	11.3%	56.9	20.1%	2.6	3.3	4.1%		22.0%	22%	106 bp	0%	80.4
18-454_S197_L004_R2_001																						17.1%	23.0%	29%	151 bp	18%	81.6
18-454_S197_L004_R2_001_val_2																							22.1%	23%	107 bp	9%	80.4
18-466_S199_L004_R1_001																						11.3%	29.1%	26%	151 bp	18%	88.6
18-466_S199_L004_R1_001_val_1	29%	83	16.8%	0.6%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	3.4	3.4	27.49%	31.4%	2.4%	9.4%	40.6	24.7%	1.7	2.2	2.6%		29.0%	22%	115 bp	0%	87.3
18-466_S199_L004_R2_001																						11.2%	29.2%	27%	151 bp	27%	88.6
18-466_S199_L004_R2_001_val_2																							29.0%	23%	116 bp	18%	87.3
18-55_S190_L004_R1_001																						18.4%	19.0%	29%	151 bp	18%	61.7
18-55_S190_L004_R1_001_val_1	30%	63	12.8%	0.4%	0.1%	0.0%	0.0%	0.0X	0.3X	100.0%	3.2	3.2	27.78%	30.0%	3.5%	15.0%	30.4	14.2%	1.6	1.9	3.1%		17.1%	22%	105 bp	0%	60.3
18-55_S190_L004_R2_001																						18.3%	18.7%	29%	151 bp	27%	61.7
18-55_S190_L004_R2_001_val_2																							17.1%	22%	106 bp	0%	60.3
18-67_S176_L004_R1_001																						28.4%	24.7%	35%	151 bp	27%	62.0
18-67_S176_L004_R1_001_val_1	31%	60	16.8%	0.7%	0.1%	0.0%	0.0%	0.0X	0.4X	100.0%	4.3	4.3	27.09%	37.4%	3.4%	15.1%	40.2	12.0%	2.2	2.5	4.6%		14.7%	23%	101 bp	0%	53.9
18-67_S176_L004_R2_001																						27.7%	23.3%	34%	151 bp	27%	62.0
18-67_S176_L004_R2_001_val_2																							13.9%	23%	101 bp	0%	53.9
18-79_S181_L004_R1_001																						19.2%	17.2%	29%	151 bp	9%	80.8
18-79_S181_L004_R1_001_val_1	30%	69	17.8%	0.9%	0.2%	0.0%	0.0%	0.0X	0.5X	100.0%	4.4	4.4	27.53%	33.2%	3.0%	15.1%	44.5	13.8%	2.2	2.6	3.2%		16.8%	23%	103 bp	0%	80.3
18-79_S181_L004_R2_001																						19.0%	16.8%	29%	151 bp	27%	80.8
18-79_S181_L004_R2_001_val_2																							16.4%	23%	103 bp	0%	80.3
18-91_S160_L004_R1_001																						35.3%	11.1%	37%	151 bp	27%	35.3
18-91_S160_L004_R1_001_val_1	30%	72	6.0%	0.1%	0.0%	0.0%	0.0%	0.0X	0.1X	100.0%	1.2	1.2	28.34%	32.2%	3.7%	13.4%	12.5	11.0%	0.6	0.6	2.4%		10.3%	24%	98 bp	0%	26.7
18-91_S160_L004_R2_001																						32.1%	11.2%	37%	151 bp	27%	35.3
18-91_S160_L004_R2_001_val_2																							9.7%	25%	101 bp	9%	26.7
18-9_S159_L004_R1_001																						46.9%	15.7%	42%	151 bp	27%	47.7
18-9_S159_L004_R1_001_val_1	31%	72	9.0%	0.2%	0.0%	0.0%	0.0%	0.0X	0.2X	100.0%	1.9	1.9	27.56%	33.6%	4.3%	14.1%	19.0	12.0%	0.9	1.1	3.7%		10.3%	26%	87 bp	9%	28.6
18-9_S159_L004_R2_001																						42.7%	16.8%	41%	151 bp	27%	47.7
18-9_S159_L004_R2_001_val_2																							10.4%	27%	92 bp	9%	28.6
L-1029_S183_L004_R1_001																						22.0%	15.5%	30%	151 bp	18%	55.8
L-1029_S183_L004_R1_001_val_1	28%	32	3.6%	0.3%	0.1%	0.0%	0.0%	0.0X	0.1X	100.0%	1.7	1.7	32.57%	28.6%	6.8%	33.8%	11.2	14.3%	0.9	1.0	1.8%		14.3%	22%	99 bp	0%	55.1
L-1029_S183_L004_R2_001																						21.8%	15.6%	29%	151 bp	27%	55.8
L-1029_S183_L004_R2_001_val_2																							14.4%	22%	99 bp	0%	55.1
L-1038_S184_L004_R1_001																						21.1%	14.7%	29%	151 bp	18%	51.4
L-1038_S184_L004_R1_001_val_1	29%	33	3.4%	0.2%	0.1%	0.0%	0.0%	0.0X	0.1X	100.0%	1.5	1.5	31.91%	27.4%	6.3%	33.0%	10.3	14.4%	0.7	0.9	1.7%		13.9%	22%	100 bp	0%	50.8
L-1038_S184_L004_R2_001																						20.8%	14.4%	29%	151 bp	27%	51.4
L-1038_S184_L004_R2_001_val_2																							13.7%	22%	101 bp	0%	50.8
L-1053_S167_L004_R1_001																						15.8%	19.3%	27%	151 bp	9%	60.1
L-1053_S167_L004_R1_001_val_1	28%	33	3.4%	0.2%	0.1%	0.0%	0.0%	0.0X	0.1X	100.0%	1.2	1.2	31.03%	30.4%	5.5%	28.9%	9.4	16.7%	0.6	0.7	1.2%		19.1%	21%	108 bp	0%	59.7
L-1053_S167_L004_R2_001																						15.7%	19.2%	27%	151 bp	9%	60.1
L-1053_S167_L004_R2_001_val_2																							18.9%	22%	108 bp	9%	59.7
L-1059_S175_L004_R1_001																						23.8%	23.6%	31%	151 bp	18%	88.7
L-1059_S175_L004_R1_001_val_1	29%	32	4.3%	0.4%	0.2%	0.0%	0.0%	0.0X	0.1X	100.0%	2.3	2.3	32.33%	25.8%	6.8%	35.9%	15.5	20.4%	1.2	1.5	1.7%		19.9%	22%	99 bp	0%	84.9
L-1059_S175_L004_R2_001																						23.6%	23.1%	31%	151 bp	27%	88.7
L-1059_S175_L004_R2_001_val_2																							19.5%	22%	99 bp	0%	84.9
L-1093_S168_L004_R1_001																						13.3%	19.4%	26%	151 bp	9%	66.1
L-1093_S168_L004_R1_001_val_1	28%	33	2.0%	0.1%	0.0%	0.0%	0.0%	0.0X	0.1X	100.0%	0.8	0.8	31.96%	26.2%	6.2%	33.1%	6.4	15.7%	0.4	0.5	0.8%		19.6%	21%	111 bp	0%	65.8
L-1093_S168_L004_R2_001																						13.2%	19.0%	26%	151 bp	18%	66.1
L-1093_S168_L004_R2_001_val_2																							19.3%	22%	112 bp	9%	65.8
L-1257_S205_L004_R1_001																						12.3%	28.5%	26%	151 bp	18%	82.9
L-1257_S205_L004_R1_001_val_1	28%	35	3.0%	0.1%	0.0%	0.0%	0.0%	0.0X	0.1X	100.0%	1.0	1.0	30.88%	30.4%	5.0%	28.2%	8.3	22.1%	0.5	0.6	0.8%		27.8%	21%	114 bp	0%	81.6
L-1257_S205_L004_R2_001																						12.3%	27.6%	26%	151 bp	18%	82.9
L-1257_S205_L004_R2_001_val_2																							26.9%	22%	114 bp	9%	81.6
L-1263_S173_L004_R1_001																						21.9%	20.5%	31%	151 bp	18%	83.5
L-1263_S173_L004_R1_001_val_1	29%	32	5.2%	0.4%	0.1%	0.0%	0.0%	0.0X	0.2X	100.0%	2.3	2.3	31.18%	26.3%	6.0%	31.3%	16.0	15.3%	1.1	1.3	1.7%		16.2%	22%	104 bp	0%	78.7
L-1263_S173_L004_R2_001																						21.6%	19.8%	31%	151 bp	27%	83.5
L-1263_S173_L004_R2_001_val_2																							15.8%	22%	104 bp	0%	78.7
L-562_S174_L004_R1_001																						28.1%	20.0%	34%	151 bp	27%	58.8
L-562_S174_L004_R1_001_val_1	29%	32	4.4%	0.4%	0.1%	0.0%	0.0%	0.0X	0.1X	100.0%	2.1	2.1	32.05%	30.5%	6.6%	34.1%	13.7	14.5%	1.0	1.2	2.2%		14.1%	22%	94 bp	0%	54.9
L-562_S174_L004_R2_001																						27.8%	19.5%	33%	151 bp	27%	58.8
L-562_S174_L004_R2_001_val_2																							14.0%	23%	95 bp	0%	54.9
L-571_S194_L004_R1_001																						18.1%	21.7%	29%	151 bp	27%	76.6
L-571_S194_L004_R1_001_val_1	28%	33	3.7%	0.3%	0.1%	0.0%	0.0%	0.0X	0.1X	100.0%	1.6	1.6	31.80%	26.3%	5.8%	31.9%	11.4	19.6%	0.8	1.0	1.3%		19.9%	22%	106 bp	0%	75.0
L-571_S194_L004_R2_001																						18.0%	21.8%	29%	151 bp	27%	76.6
L-571_S194_L004_R2_001_val_2																							20.2%	22%	106 bp	0%	75.0
L-661_S182_L004_R1_001																						13.9%	20.6%	27%	151 bp	18%	67.5
L-661_S182_L004_R1_001_val_1	29%	62	6.2%	0.2%	0.0%	0.0%	0.0%	0.0X	0.1X	100.0%	1.5	1.5	29.11%	27.8%	3.4%	19.9%	14.9	16.6%	0.7	0.9	1.3%		20.6%	22%	110 bp	0%	67.2
L-661_S182_L004_R2_001																						13.8%	20.8%	26%	151 bp	9%	67.5
L-661_S182_L004_R2_001_val_2																							20.8%	22%	111 bp	0%	67.2
L-704_S169_L004_R1_001																						14.2%	19.9%	26%	151 bp	18%	64.9
L-704_S169_L004_R1_001_val_1	27%	31	1.6%	0.1%	0.0%	0.0%	0.0%	0.0X	0.1X	100.0%	0.9	0.9	33.89%	22.3%	9.1%	37.1%	5.7	16.4%	0.5	0.5	0.8%		19.8%	21%	110 bp	0%	64.5
L-704_S169_L004_R2_001																						14.1%	19.5%	27%	151 bp	18%	64.9
L-704_S169_L004_R2_001_val_2																							19.4%	21%	110 bp	9%	64.5
L-728_S161_L004_R1_001																						42.1%	13.4%	38%	151 bp	27%	47.0
L-728_S161_L004_R1_001_val_1	29%	32	2.2%	0.1%	0.0%	0.0%	0.0%	0.0X	0.1X	100.0%	0.9	0.9	32.61%	29.2%	8.7%	34.0%	6.2	13.2%	0.4	0.5	1.4%		11.4%	24%	84 bp	0%	36.1
L-728_S161_L004_R2_001																						37.2%	13.9%	38%	151 bp	27%	47.0
L-728_S161_L004_R2_001_val_2																							11.0%	25%	89 bp	9%	36.1
L-862_S200_L004_R1_001																						15.3%	16.0%	28%	151 bp	18%	40.2
L-862_S200_L004_R1_001_val_1	29%	35	1.9%	0.1%	0.0%	0.0%	0.0%	0.0X	0.1X	100.0%	0.6	0.6	31.02%	29.8%	5.4%	31.2%	5.2	12.8%	0.3	0.4	0.9%		15.0%	22%	110 bp	0%	39.3
L-862_S200_L004_R2_001																						15.1%	15.5%	28%	151 bp	18%	40.2
L-862_S200_L004_R2_001_val_2																							14.6%	22%	111 bp	9%	39.3
L-924_S204_L004_R1_001																						23.3%	18.7%	31%	151 bp	18%	63.5
L-924_S204_L004_R1_001_val_1	29%	32	2.8%	0.3%	0.1%	0.0%	0.0%	0.0X	0.1X	100.0%	1.5	1.5	33.14%	23.0%	7.3%	37.2%	10.0	15.9%	0.7	0.9	1.4%		16.4%	23%	97 bp	0%	62.5
L-924_S204_L004_R2_001																						23.1%	18.5%	31%	151 bp	18%	63.5
L-924_S204_L004_R2_001_val_2																							16.6%	23%	98 bp	0%	62.5
L-933_S203_L004_R1_001																						21.0%	21.5%	29%	151 bp	18%	76.6
L-933_S203_L004_R1_001_val_1	28%	32	3.3%	0.3%	0.1%	0.0%	0.0%	0.0X	0.1X	100.0%	1.5	1.5	32.68%	25.7%	6.3%	33.8%	10.4	16.4%	0.8	0.9	1.2%		19.3%	22%	101 bp	0%	74.9
L-933_S203_L004_R2_001																						20.9%	21.5%	29%	151 bp	27%	76.6
L-933_S203_L004_R2_001_val_2																							19.3%	22%	102 bp	0%	74.9

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order.

Sort	Group	Column	Description	ID	Scale
\|\|	QualiMap	% GC	Mean GC content	`avg_gc`	None
\|\|	QualiMap	Ins. size	Median insert size	`median_insert_size`	None
\|\|	QualiMap	≥ 1X	Fraction of genome with at least 1X coverage	`1_x_pc`	None
\|\|	QualiMap	≥ 5X	Fraction of genome with at least 5X coverage	`5_x_pc`	None
\|\|	QualiMap	≥ 10X	Fraction of genome with at least 10X coverage	`10_x_pc`	None
\|\|	QualiMap	≥ 30X	Fraction of genome with at least 30X coverage	`30_x_pc`	None
\|\|	QualiMap	≥ 50X	Fraction of genome with at least 50X coverage	`50_x_pc`	None
\|\|	QualiMap	Median cov	Median coverage	`median_coverage`	None
\|\|	QualiMap	Mean cov	Mean coverage	`mean_coverage`	None
\|\|	QualiMap	% Aligned	% mapped reads	`percentage_aligned`	None
\|\|	QualiMap	M Aligned	Number of mapped reads (millions)	`mapped_reads`	read_count
\|\|	QualiMap	M Total reads	Number of reads (millions)	`total_reads`	read_count
\|\|	QualiMap	Error rate	Alignment error rate. Total edit distance (SAM NM field) over the number of mapped bases	`general_error_rate`	None
\|\|	Bismark	% mCpG	% Cytosines methylated in CpG context	`percent_cpg_meth`	None
\|\|	Bismark	% mCHG	% Cytosines methylated in CHG context	`percent_chg_meth`	None
\|\|	Bismark	% mCHH	% Cytosines methylated in CHH context	`percent_chh_meth`	None
\|\|	Bismark	M C's	Total number of C's analysed, in millions	`total_c`	None
\|\|	Bismark	% Dups	Percent Duplicated Alignments	`dup_reads_percent`	None
\|\|	Bismark	M Unique	Deduplicated Alignments (millions)	`dedup_reads`	read_count
\|\|	Bismark	M Aligned	Total Aligned Sequences (millions)	`aligned_reads`	read_count
\|\|	Bismark	% Aligned	Percent Aligned Sequences	`percent_aligned`	None
\|\|	Cutadapt	% BP Trimmed	% Total Base Pairs trimmed	`percent_trimmed`	None
\|\|	FastQC	% Dups	% Duplicate Reads	`percent_duplicates`	None
\|\|	FastQC	% GC	Average % GC Content	`percent_gc`	None
\|\|	FastQC	Length	Average Sequence Length (bp)	`avg_sequence_length`	None
\|\|	FastQC	% Failed	Percentage of modules failed in FastQC report (includes those not plotted here)	`percent_fails`	None
\|\|	FastQC	M Seqs	Total Sequences (millions)	`total_sequences`	read_count

QualiMap

QualiMap is a platform-independent application to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.

Coverage histogram

Distribution of the number of locations in the reference genome with a given depth of coverage.

Bases of a reference sequence (y-axis) are groupped by their depth of coverage (0×, 1×, …, N×) (x-axis). This plot shows the frequency of coverage depths relative to the reference sequence for each read dataset, which provides an indirect measure of the level and variation of coverage depth in the corresponding sequenced sample.

If reads are randomly distributed across the reference sequence, this plot should resemble a Poisson distribution (Lander & Waterman 1988), with a peak indicating approximate depth of coverage, and more uniform coverage depth being reflected in a narrower spread. The optimal level of coverage depth depends on the aims of the experiment, though it should at minimum be sufficiently high to adequately address the biological question; greater uniformity of coverage is generally desirable, because it increases breadth of coverage for a given depth of coverage, allowing equivalent results to be achieved at a lower sequencing depth (Sampson et al. 2011; Sims et al. 2014). However, it is difficult to achieve uniform coverage depth in practice, due to biases introduced during sample preparation (van Dijk et al. 2014), sequencing (Ross et al. 2013) and read mapping (Sims et al. 2014).

This plot may include a small peak for regions of the reference sequence with zero depth of coverage. Such regions may be absent from the given sample (due to a deletion or structural rearrangement), present in the sample but not successfully sequenced (due to bias in sequencing or preparation), or sequenced but not successfully mapped to the reference (due to the choice of mapping algorithm, the presence of repeat sequences, or mismatches caused by variants or sequencing errors). Related factors cause most datasets to contain some unmapped reads (Sims et al. 2014).

Cumulative genome coverage

Percentage of the reference genome with at least the given depth of coverage.

For a set of DNA or RNA reads mapped to a reference sequence, such as a genome or transcriptome, the depth of coverage at a given base position is the number of high-quality reads that map to the reference at that position, while the breadth of coverage is the fraction of the reference sequence to which reads have been mapped with at least a given depth of coverage (Sims et al. 2014).

Defining coverage breadth in terms of coverage depth is useful, because sequencing experiments typically require a specific minimum depth of coverage over the region of interest (Sims et al. 2014), so the extent of the reference sequence that is amenable to analysis is constrained to lie within regions that have sufficient depth. With inadequate sequencing breadth, it can be difficult to distinguish the absence of a biological feature (such as a gene) from a lack of data (Green 2007).

For increasing coverage depths (1×, 2×, …, N×), coverage breadth is calculated as the percentage of the reference sequence that is covered by at least that number of reads, then plots coverage breadth (y-axis) against coverage depth (x-axis). This plot shows the relationship between sequencing depth and breadth for each read dataset, which can be used to gauge, for example, the likely effect of a minimum depth filter on the fraction of a genome available for analysis.

Insert size histogram

Distribution of estimated insert sizes of mapped reads.

To overcome limitations in the length of DNA or RNA sequencing reads, many sequencing instruments can produce two or more shorter reads from one longer fragment in which the relative position of reads is approximately known, such as paired-end or mate-pair reads (Mardis 2013). Such techniques can extend the reach of sequencing technology, allowing for more accurate placement of reads (Reinert et al. 2015) and better resolution of repeat regions (Reinert et al. 2015), as well as detection of structural variation (Alkan et al. 2011) and chimeric transcripts (Maher et al. 2009).

All these methods assume that the approximate size of an insert is known. (Insert size can be defined as the length in bases of a sequenced DNA or RNA fragment, excluding technical sequences such as adapters, which are typically removed before alignment.) This plot allows for that assumption to be assessed. With the set of mapped fragments for a given sample, QualiMap groups the fragments by insert size, then plots the frequency of mapped fragments (y-axis) over a range of insert sizes (x-axis). In an ideal case, the distribution of fragment sizes for a sequencing library would culminate in a single peak indicating average insert size, with a narrow spread indicating highly consistent fragment lengths.

QualiMap calculates insert sizes as follows: for each fragment in which every read mapped successfully to the same reference sequence, it extracts the insert size from the TLEN field of the leftmost read (see the Qualimap 2 documentation), where the TLEN (or 'observed Template LENgth') field contains 'the number of bases from the leftmost mapped base to the rightmost mapped base' (SAM format specification). Note that because it is defined in terms of alignment to a reference sequence, the value of the TLEN field may differ from the insert size due to factors such as alignment clipping, alignment errors, or structural variation or splicing in a gap between reads from the same fragment.

GC content distribution

Each solid line represents the distribution of GC content of mapped reads for a given sample.

GC bias is the difference between the guanine-cytosine content (GC-content) of a set of sequencing reads and the GC-content of the DNA or RNA in the original sample. It is a well-known issue with sequencing systems, and may be introduced by PCR amplification, among other factors (Benjamini & Speed 2012; Ross et al. 2013).

QualiMap calculates the GC-content of individual mapped reads, then groups those reads by their GC-content (1%, 2%, …, 100%), and plots the frequency of mapped reads (y-axis) at each level of GC-content (x-axis). This plot shows the GC-content distribution of mapped reads for each read dataset, which should ideally resemble that of the original sample. It can be useful to display the GC-content distribution of an appropriate reference sequence for comparison, and QualiMap has an option to do this (see the Qualimap 2 documentation).

Preseq

Preseq estimates the complexity of a library, showing how many additional unique reads are sequenced for increasing total read count. A shallow curve indicates complexity saturation. The dashed line shows a perfectly complex library where total reads = unique reads.

Complexity curve

Note that the x axis is trimmed at the point where all the datasets show 80% of their maximum y-value, to avoid ridiculous scales.

Bismark

Bismark is a tool to map bisulfite converted sequence reads and determine cytosine methylation states.

Alignment Rates

Deduplication

Strand Alignment

Cytosine Methylation

M-Bias

This plot shows the average percentage methylation and coverage across reads. See the bismark user guide for more information on how these numbers are generated.

Cutadapt

Cutadapt is a tool to find and remove adapter sequences, primers, poly-Atails and other types of unwanted sequence from your high-throughput sequencing reads.

Filtered Reads

This plot shows the number of reads (SE) / pairs (PE) removed by Cutadapt.

Trimmed Sequence Lengths

This plot shows the number of reads with certain lengths of adapter trimmed.

Obs/Exp shows the raw counts divided by the number expected due to sequencing errors. A defined peak may be related to adapter length.

See the cutadapt documentation for more information on how these numbers are generated.

FastQC

FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

Sequence Counts

Sequence counts for each sample. Duplicate read counts are an estimate only.

This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

Sequence Quality Histograms

The mean quality value across each base position in the read.

To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

Taken from the FastQC help:

The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

Per Sequence Quality Scores

The number of reads with average quality scores. Shows if a subset of reads has poor quality.

From the FastQC help:

The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

Per Base Sequence Content

The proportion of each base position for which each of the four normal DNA bases has been called.

To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

To see the data as a line plot, as in the original FastQC graph, click on a sample track.

From the FastQC help:

Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

Click a sample row to see a line plot for that dataset.

Rollover for sample name

Position: -

%T: -

%C: -

%A: -

%G: -

Per Sequence GC Content

The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

From the FastQC help:

This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

Per Base N Content

The percentage of base calls at each position for which an N was called.

From the FastQC help:

If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

Sequence Length Distribution

The distribution of fragment sizes (read lengths) found. See the FastQC help

Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

Sequence Duplication Levels

The relative level of duplication found for every sequence.

From the FastQC Help:

In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

Overrepresented sequences

The total amount of overrepresented sequences found in each library.

FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as over represented.

Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

From the FastQC Help:

A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

FastQC lists all of the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

Adapter Content

The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

Note that only samples with ≥ 0.1% adapter contamination are shown.

There may be several lines per sample, as one is shown for each adapter detected in the file.

From the FastQC Help:

The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

Status Checks

Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

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